Diagnosis and treatment of impulse control disorders in patients with movement disorders
Bibliographic record
Abstract
Impulse control disorders are a psychiatric condition characterized by the failure to resist an impulsive act or behavior that may be harmful to self or others. In movement disorders, impulse control disorders are associated with dopaminergic treatment, notably dopamine agonists (DAs). Impulse control disorders have been studied extensively in Parkinson's disease, but are also recognized in restless leg syndrome and atypical Parkinsonian syndromes. Epidemiological studies suggest younger age, male sex, greater novelty seeking, impulsivity, depression and premorbid impulse control disorders as the most consistent risk factors. Such patients may warrant special monitoring after starting treatment with a DA. Various individual screening tools are available for people without Parkinson's disease. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease has been developed specifically for Parkinson's disease. The best treatment for impulse control disorders is prevention. However, after the development of impulse control disorders, the mainstay intervention is to reduce or discontinue the offending anti-Parkinsonian medication. In refractory cases, other pharmacological interventions are available, including neuroleptics, antiepileptics, amantadine, antiandrogens, lithium and opioid antagonists. Unfortunately, their use is only supported by case reports, small case series or open-label clinical studies. Prospective, controlled studies are warranted. Ongoing investigations include naltrexone and nicotine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".